{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import tensorflow\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.layers import Embedding,Bidirectional,LSTM,Dense,Dropout\n",
    "from tensorflow.keras.utils import to_categorical"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "                                       clean_comment  category\n0   family mormon have never tried explain them t...         1\n1  buddhism has very much lot compatible with chr...         1\n2  seriously don say thing first all they won get...        -1\n3  what you have learned yours and only yours wha...         0\n4  for your own benefit you may want read living ...         1",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>clean_comment</th>\n      <th>category</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>family mormon have never tried explain them t...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>buddhism has very much lot compatible with chr...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>seriously don say thing first all they won get...</td>\n      <td>-1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>what you have learned yours and only yours wha...</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>for your own benefit you may want read living ...</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Reddit_Data.csv')\n",
    "df.head(5)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8277, 13142, 15830]\n"
     ]
    }
   ],
   "source": [
    "dist=list(df.category)\n",
    "pp=[0,0,0]\n",
    "for i in dist:\n",
    "    if i==-1:\n",
    "        pp[0]+=1\n",
    "    elif i==0:\n",
    "        pp[1]+=1\n",
    "    else:\n",
    "        pp[2]+=1\n",
    "print(pp)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels=['Negative','Neutral','Positive']\n",
    "sns.barplot(x=labels,y=pp)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(' family mormon have never tried explain them they still stare puzzled from time time like some kind strange creature nonetheless they have come admire for the patience calmness equanimity acceptance and compassion have developed all the things buddhism teaches ', 1), ('buddhism has very much lot compatible with christianity especially considering that sin and suffering are almost the same thing suffering caused wanting things shouldn want going about getting things the wrong way christian this would mean wanting things that don coincide with god will and wanting things that coincide but without the aid jesus buddhism could also seen proof god all mighty will and omnipotence certainly christians are lucky have one such christ there side but what about everyone else well many christians believe god grace salvation and buddhism god way showing grace upon others would also help study the things jesus said and see how buddha has made similar claims such rich man getting into heaven joke basically advocating that should rid ourselves material possessions fact distinctly remembered jesus making someone cry because that someone asked what achieve salvation and jesus replied with live like buddhist very very roughly translated also point out that buddha rarely spoke anything about god theory personally because knew well enough leave that jesus and mohamed who came later just remember conflict difference opinion but education can fun involving and enlightening easier teach something than prove right like intelligent design ', 1), ('seriously don say thing first all they won get its too complex explain normal people anyway and they are dogmatic then doesn matter what you say see mechante post and for any reason you decide later life move from buddhism and that doesn suit you identity though you still get keep all the wisdom then your family will treat you like you went through weird hippy phase for while there didncha and you never hear the end pro tip don put one these your wall jpg ', -1), ('what you have learned yours and only yours what you want teach different focus the goal not the wrapping paper buddhism can passed others without word about the buddha ', 0), ('for your own benefit you may want read living buddha living christ thich nhat hanh you might find any subsequent discussions with your loved ones easier you are able articulate some the parallels that exist between buddhism and christianity don surprised they react negatively for having lost you treat them with compassion and deserved understanding although they may indeed display signs being hurt your new path properly sharing with them way that may alleviate their fear something they may perceive wrong the very least alien their beliefs may help allowing them the long run accept although not necessarily agree with your decision regardless where they end you have make your own way ', 1)]\n"
     ]
    }
   ],
   "source": [
    "comment=list(df.clean_comment.astype(str))\n",
    "sentiment=list(df.category)\n",
    "reddit_dict=dict(zip(comment,sentiment))\n",
    "print(list(reddit_dict.items())[:5])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['seriously don say thing first all they won get its too complex explain normal people anyway and they are dogmatic then doesn matter what you say see mechante post and for any reason you decide later life move from buddhism and that doesn suit you identity though you still get keep all the wisdom then your family will treat you like you went through weird hippy phase for while there didncha and you never hear the end pro tip don put one these your wall jpg ', 'you should all sit down together and watch the simpsons episode where lisa becomes buddhist simpsons season episode she little faith then discuss '] \n",
      " ['what you have learned yours and only yours what you want teach different focus the goal not the wrapping paper buddhism can passed others without word about the buddha ', 'jesus was zen meets jew '] \n",
      " [' family mormon have never tried explain them they still stare puzzled from time time like some kind strange creature nonetheless they have come admire for the patience calmness equanimity acceptance and compassion have developed all the things buddhism teaches ', 'buddhism has very much lot compatible with christianity especially considering that sin and suffering are almost the same thing suffering caused wanting things shouldn want going about getting things the wrong way christian this would mean wanting things that don coincide with god will and wanting things that coincide but without the aid jesus buddhism could also seen proof god all mighty will and omnipotence certainly christians are lucky have one such christ there side but what about everyone else well many christians believe god grace salvation and buddhism god way showing grace upon others would also help study the things jesus said and see how buddha has made similar claims such rich man getting into heaven joke basically advocating that should rid ourselves material possessions fact distinctly remembered jesus making someone cry because that someone asked what achieve salvation and jesus replied with live like buddhist very very roughly translated also point out that buddha rarely spoke anything about god theory personally because knew well enough leave that jesus and mohamed who came later just remember conflict difference opinion but education can fun involving and enlightening easier teach something than prove right like intelligent design ']\n"
     ]
    }
   ],
   "source": [
    "Neg_list=[]\n",
    "Pos_list=[]\n",
    "Neutral_list=[]\n",
    "for i,j in reddit_dict.items():\n",
    "    if j==-1:\n",
    "        Neg_list.append(i)\n",
    "    elif j==0:\n",
    "        Neutral_list.append(i)\n",
    "    else:\n",
    "        Pos_list.append(i)\n",
    "print(Neg_list[:2],'\\n',Neutral_list[:2],'\\n',Pos_list[:2])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "pos_len=[]\n",
    "for i in Pos_list:\n",
    "    pos_len.append(len(i))\n",
    "neg_len=[]\n",
    "for i in Neg_list:\n",
    "    neg_len.append(len(i))\n",
    "Neutral_len=[]\n",
    "for i in Neutral_list:\n",
    "    Neutral_len.append(len(i))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1440x576 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(20,8))\n",
    "plt.title(\"Word Length Variation\")\n",
    "plt.plot(Neutral_len[:250],c='b',label='Neutral')\n",
    "plt.plot(neg_len[:250],c='r',label='Negative')\n",
    "plt.plot(pos_len[:250],c='g',label='Positive')\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos_mean=sum(pos_len)//len(pos_len)\n",
    "neg_mean=sum(neg_len)//len(neg_len)\n",
    "neutral_mean=sum(Neutral_len)//len(Neutral_len)\n",
    "combined_mean=(sum(pos_len)+sum(neg_len)+sum(Neutral_len))//(len(pos_len)+len(neg_len)+len(Neutral_len))\n",
    "plt.title(\"Average Word Length\")\n",
    "sns.barplot(x=['Negative','Neutral','Positive','Combined'],y=[neg_mean,neutral_mean,pos_mean,combined_mean])\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "0     family mormon have never tried explain them t...\n1    buddhism has very much lot compatible with chr...\n2    seriously don say thing first all they won get...\n3    what you have learned yours and only yours wha...\n4    for your own benefit you may want read living ...\nName: clean_comment, dtype: object"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X=df['clean_comment'].astype('str')\n",
    "X[:5]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " family mormon have never tried explain them they still stare puzzled from time time like some kind \n"
     ]
    },
    {
     "data": {
      "text/plain": "(55543, 1134781)"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lp=\"\"\n",
    "for i in X:\n",
    "    lp+=i+\" \"\n",
    "print(lp[:100])\n",
    "\n",
    "st=lp.split(' ')\n",
    "dict_len=len(set(st))\n",
    "dict_len,len(st)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "54720"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer=Tokenizer(num_words=dict_len,lower=True,oov_token=\"OOV\")\n",
    "tokenizer.fit_on_texts(X)\n",
    "len(tokenizer.word_index)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "[[255,\n  27343,\n  11,\n  123,\n  642,\n  871,\n  40,\n  10,\n  95,\n  12295,\n  16336,\n  24,\n  54,\n  54,\n  22,\n  43,\n  290,\n  4165,\n  14016,\n  7561,\n  10,\n  11,\n  129,\n  3150,\n  6,\n  2,\n  5394,\n  19936,\n  11063,\n  6437,\n  3,\n  4417,\n  11,\n  1440,\n  19,\n  2,\n  112,\n  1519,\n  8055],\n [1519,\n  20,\n  78,\n  73,\n  83,\n  7127,\n  12,\n  2851,\n  454,\n  1144,\n  4,\n  7128,\n  3,\n  1710,\n  8,\n  383,\n  2,\n  45,\n  93,\n  1710,\n  1857,\n  2984,\n  112,\n  961,\n  91,\n  88,\n  26,\n  191,\n  112,\n  2,\n  202,\n  79,\n  1320,\n  5,\n  36,\n  263,\n  2984,\n  112,\n  4,\n  39,\n  19937,\n  12,\n  303,\n  14,\n  3,\n  2984,\n  112,\n  4,\n  19937,\n  13,\n  182,\n  2,\n  2852,\n  2381,\n  1519,\n  120,\n  60,\n  246,\n  709,\n  303,\n  19,\n  5184,\n  14,\n  3,\n  19938,\n  1407,\n  1469,\n  8,\n  2382,\n  11,\n  31,\n  102,\n  4290,\n  28,\n  363,\n  13,\n  17,\n  26,\n  190,\n  285,\n  76,\n  92,\n  1469,\n  198,\n  303,\n  6438,\n  11064,\n  3,\n  1519,\n  303,\n  79,\n  891,\n  6438,\n  1145,\n  280,\n  36,\n  60,\n  228,\n  1520,\n  2,\n  112,\n  2381,\n  87,\n  3,\n  67,\n  33,\n  882,\n  20,\n  137,\n  552,\n  883,\n  102,\n  851,\n  136,\n  191,\n  104,\n  3939,\n  832,\n  700,\n  6780,\n  4,\n  58,\n  1858,\n  1859,\n  1582,\n  14017,\n  256,\n  19939,\n  7129,\n  2381,\n  252,\n  133,\n  1751,\n  48,\n  4,\n  133,\n  435,\n  17,\n  1691,\n  11064,\n  3,\n  2381,\n  4990,\n  12,\n  284,\n  22,\n  1679,\n  78,\n  78,\n  5877,\n  6140,\n  60,\n  183,\n  41,\n  4,\n  882,\n  3286,\n  1787,\n  155,\n  26,\n  303,\n  1731,\n  872,\n  48,\n  997,\n  76,\n  247,\n  747,\n  4,\n  2381,\n  3,\n  14018,\n  29,\n  345,\n  585,\n  27,\n  364,\n  2266,\n  440,\n  339,\n  13,\n  524,\n  23,\n  609,\n  4166,\n  3,\n  12296,\n  1378,\n  2206,\n  116,\n  62,\n  1095,\n  71,\n  22,\n  2340,\n  2617]]"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train=tokenizer.texts_to_sequences(X)\n",
    "X_train_padded=pad_sequences(X_train,maxlen=175,padding='post',truncating='post')\n",
    "X_train[:2]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 1. 0.]\n",
      " [0. 1. 0.]\n",
      " [0. 0. 1.]]\n"
     ]
    }
   ],
   "source": [
    "df['category']=df['category'].replace({-1:2})\n",
    "mp={0:\"Neutral\",1:\"Positve\",2:\"Negative\"}\n",
    "Y=df['category'].values\n",
    "Y_hot=to_categorical(Y)\n",
    "print(Y_hot[:3])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " embedding (Embedding)       (None, 175, 64)           3554752   \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 175, 64)           0         \n",
      "                                                                 \n",
      " bidirectional (Bidirectiona  (None, 200)              132000    \n",
      " l)                                                              \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 200)               0         \n",
      "                                                                 \n",
      " dense (Dense)               (None, 3)                 603       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 3,687,355\n",
      "Trainable params: 3,687,355\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "model=Sequential()\n",
    "model.add(Embedding(dict_len,64,input_length=175))#全连接层\n",
    "model.add(Dropout(0.3))\n",
    "model.add(Bidirectional(LSTM(100,return_sequences=False)))\n",
    "model.add(Dropout(0.3))\n",
    "model.add(Dense(3,activation='softmax'))#添加神经网络，提取特征\n",
    "print(model.summary())"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "932/932 [==============================] - 121s 127ms/step - loss: 0.5829 - accuracy: 0.7577 - val_loss: 0.2899 - val_accuracy: 0.9075\n",
      "Epoch 2/5\n",
      "932/932 [==============================] - 117s 126ms/step - loss: 0.2185 - accuracy: 0.9284 - val_loss: 0.2318 - val_accuracy: 0.9263\n",
      "Epoch 3/5\n",
      "932/932 [==============================] - 118s 127ms/step - loss: 0.1244 - accuracy: 0.9621 - val_loss: 0.2663 - val_accuracy: 0.9217\n",
      "Epoch 4/5\n",
      "932/932 [==============================] - 119s 127ms/step - loss: 0.0836 - accuracy: 0.9752 - val_loss: 0.2842 - val_accuracy: 0.9286\n",
      "Epoch 5/5\n",
      "932/932 [==============================] - 118s 126ms/step - loss: 0.0663 - accuracy: 0.9804 - val_loss: 0.3422 - val_accuracy: 0.9153\n"
     ]
    }
   ],
   "source": [
    "model.compile(optimizer='adam',metrics=['accuracy'],loss='categorical_crossentropy')\n",
    "hist=model.fit(X_train_padded,Y_hot,epochs=5,validation_split=0.2)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(hist.history['accuracy'],c='b',label='Training')\n",
    "plt.plot(hist.history['val_accuracy'],c='r',label='Validation')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(hist.history['loss'],c='b',label='Training')\n",
    "plt.plot(hist.history['val_loss'],c='r',label='Validation')\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [],
   "source": [
    "def predict(s):\n",
    "    X_tes=[]\n",
    "    X_tes.append(s)\n",
    "    X_test=tokenizer.texts_to_sequences(X_tes)\n",
    "    X_test_padded=pad_sequences(X_test,maxlen=175,padding='post',truncating='post')\n",
    "    predict_x=model.predict(X_test_padded)\n",
    "    classes_x=np.argmax(predict_x,axis=1)\n",
    "    sent=int(classes_x)\n",
    "    print(\"The Predicted Sentiment is \",mp[sent])\n",
    "#pol=\"The article is good but its not great moreover i would say you have done a decent job\"\n",
    "#predict(pol)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Predicted Sentiment is  Positve\n"
     ]
    }
   ],
   "source": [
    "pol=\"The article is good but its not great moreover i would say you have done a decent job\"\n",
    "predict(pol)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "lop=\"You have done a stupid mistake which made you lose all the progress you made\"\n",
    "predict(lop)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}